The expression of genes involves a sequence of enzymatic events, such as transcription, mRNA processing, mRNA decay, and translation, that are subject to gene regulatory networks (GRNs) of protein-nucleic acid interactions. It is well appreciated that the control of transcription via regulatory networks that regulate enhancer and promoter activities are not the sole determinant of what gene products result, but that exon skipping is pervasive and post-transcriptional mechanisms such as mRNA splicing and decay determine the kinetics of mRNA induction and abundance. Indeed, in our preliminary studies of the macrophage response to pathogens, we find that a majority of induced gene expression events result in mRNAs that deviate substantially from those predicted by the genome-browser, and that mRNA decay is controlled by both protein- nucleic acid and miRNA regulatory networks. The proposed Center for the Ribonomics of Gene Regulation leverages and pioneers Next Gen Sequencing and computational modeling approaches to develop a predictive model for which mRNA isoforms are expressed and at what level given a given promoter activity and transcription initiation rate. We will develop generally applicable tools in conjunction with or in depth and quantitative experimental analysis of the macrophage response to pathogen-associated endotoxin, which results in the dramatic up regulation of more than 1000 genes. Strikingly, our preliminary data identified more than 900 exon skipping events in addition to numerous cases of alternative 5' or 3' splice site use, emphasizing the essential contribution of post-initiation events. Further, these splice patterns are dependent on the macrophage subtype-specific chromatin landscape and are altered by inducible splice factors in primed or tolerated states. Thus we will leverage the well-described macrophage biology and associated experimental model systems, to examine the role of gene structure and sequence (Aim 1), the role of chromatin modifications (Aim 2), and of trans-acting splicing factors (Aim 3) in determining the identity of mature mRNAs and their associated synthesis rates, before adding the stimulus-responsive regulatory networks that confer mRNA half-life control and thus determine the abundance of each mRNA isoform (Aim 4).